ASL-Homework-RGBD Dataset: An Annotated Dataset of 45 Fluent and Non-fluent Signers Performing American Sign Language Homeworks

Hassan, Saad | Seita, Matthew | Berke, Larwan | Tian, Yingli | Gale, Elaine | Lee, Sooyeon | Huenerfauth, Matt

Volume:: Proceedings of the LREC2022 10th Workshop on the Representation and Processing of Sign Languages: Multilingual Sign Language Resources
Venue:: Marseille, France
Date:: 25 June 2022
Pages:: 67–72
Publisher:: European Language Resources Association (ELRA)
License:: CC BY-NC 4.0
sign-lang ID:: 22008
ACL ID:: 2022.signlang-1.11
ISBN:: 979-10-95546-86-3

Content Categories

Languages:: American Sign Language
Corpora:: ASL-Homework-RGBD Dataset

Abstract

We are releasing a dataset containing videos of both fluent and non-fluent signers using American Sign Language (ASL), which were collected using a Kinect v2 sensor. This dataset was collected as a part of a project to develop and evaluate computer vision algorithms to support new technologies for automatic detection of ASL fluency attributes. A total of 45 fluent and non-fluent participants were asked to perform signing homework assignments that are similar to the assignments used in introductory or intermediate level ASL courses. The data is annotated to identify several aspects of signing including grammatical features and non-manual markers. Sign language recognition is currently very data-driven and this dataset can support the design of recognition technologies, especially technologies that can benefit ASL learners. This dataset might also be interesting to ASL education researchers who want to contrast fluent and non-fluent signing.

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Citation in ACL Citation Format

Saad Hassan, Matthew Seita, Larwan Berke, Yingli Tian, Elaine Gale, Sooyeon Lee, Matt Huenerfauth. 2022. ASL-Homework-RGBD Dataset: An Annotated Dataset of 45 Fluent and Non-fluent Signers Performing American Sign Language Homeworks. In Proceedings of the LREC2022 10th Workshop on the Representation and Processing of Sign Languages: Multilingual Sign Language Resources, pages 67–72, Marseille, France. European Language Resources Association (ELRA).

BibTeX Export

@inproceedings{hassan:22008:sign-lang:lrec,
  author    = {Hassan, Saad and Seita, Matthew and Berke, Larwan and Tian, Yingli and Gale, Elaine and Lee, Sooyeon and Huenerfauth, Matt},
  title     = {{ASL-Homework-RGBD} Dataset: An Annotated Dataset of 45 Fluent and Non-fluent Signers Performing {American} {Sign} {Language} Homeworks},
  pages     = {67--72},
  editor    = {Efthimiou, Eleni and Fotinea, Stavroula-Evita and Hanke, Thomas and Hochgesang, Julie A. and Kristoffersen, Jette and Mesch, Johanna and Schulder, Marc},
  booktitle = {Proceedings of the {LREC2022} 10th Workshop on the Representation and Processing of Sign Languages: Multilingual Sign Language Resources},
  maintitle = {13th International Conference on Language Resources and Evaluation ({LREC} 2022)},
  publisher = {{European Language Resources Association (ELRA)}},
  address   = {Marseille, France},
  day       = {25},
  month     = jun,
  year      = {2022},
  isbn      = {979-10-95546-86-3},
  language  = {english},
  url       = {https://www.sign-lang.uni-hamburg.de/lrec/pub/22008.pdf}
}